Split CIFAR-100 (10 tasks x 10 classes, class-incremental)

Canonical class-incremental continual learning benchmark: CIFAR-100 is split into 10 sequential tasks of 10 classes each. Models learn tasks one at a time without access to prior-task data and are evaluated on average accuracy across all tasks after the full sequence.